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Create unique and engaging segment with ChatGPT, a pre-trained language model by OpenAI for generating high-quality and accurate content.
A/B Testing for Email Segmentation
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Understanding Email List Segmentation and Its Benefits for Email Campaign Metrics
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Best Practices for Using Email Lead Magnets to Segment Your Email List
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Using Email List Segmentation to Improve Email Campaign Performance
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Generating an Opinion About Email List Segmentation Strategies to Improve Customer Retention
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How Can I Use Email List Segmentation to Optimize My Email Marketing Budget?
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How to Use Email Marketing Automation Workflows to Segment Your Email List
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Best Practices for Using Email Marketing Data to Segment an Email List
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Using Email Marketing Data Analysis to Segment Your Email List
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Best Practices for Using Email Opt-in Incentives to Segment an Email List
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Generating an Opinion about Email Lead Magnets for Segmenting Email Lists
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Using Email Personalization to Segment Your Email List - Strategies and Tips
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Generating an Opinion about Email Content Upgrades for Segmenting an Email List
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Using Email Marketing Metrics to Segment Your Email List
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How to Use Email List Segmentation to Improve Click-Through Rates
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Best Practices for Using Email Segmentation to Build an Email List
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Creating an Opinion About Email List Segmentation Strategies to Improve Conversion Rates
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Segmenting Your Email List for Better Targeting and Engagement
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How to Use Email List Segmentation to Increase the Impact of Email Campaigns
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Creating More Personalized and Engaging Email Campaigns with Email List Segmentation
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What is “prompt engineering”?
A “prompt” is the input that guides a generative AI model to generate useful outputs. Generative AI tools like ChatGPT, GPT, DALL·E 2, Stable Diffusion, Midjourney, etc. all require prompting as their input.
In a natural language processing (NLP) context, “prompt engineering” is the process of discovering inputs that yield desirable or useful results. As is the story with any processes, better inputs yield better outputs; or commonly said another way “garbage in, garbage out.”
![Source: https://www.youtube.com/watch?v=1NQWJjgi-_k
Designing effective and efficient prompts will increase the likelihood of receiving a response that is both favorable and contextual. With a good prompt, you can spend less time editing content and more time generating it.
Going from beginner → advanced prompt engineer
As companies like PromptBase arise around the idea that the prompt is the “secret sauce” to using generative AI, prompt engineering could easily become the “career of the future.” But, any generative AI user can become an “advanced” prompt engineer. Here’s how
Spend time with the tools
- The more time you spend asking ChatGPT questions and receiving responses, the better your idea will be of various prompting approaches and their individual strengths and weaknesses
- Use Open AI’s GPT playground to perform interactive trial and error with variations in your prompt, model, temperature and top_p values (uniqueness of answer, i.e. creativity), and more available within the UI itself.
Become a prompt researcher instead of engineer
- If you’re already a subject matter expert in something, consider figuring out how to apply your personal skills to generating the best prompts in your field
- For example, if you’re an expert in SEO, what questions do you ask yourself when creating SEO strategies? How can you translate this knowledge into better prompts to generate the same level of output with AI?
Become a prompt researcher instead of engineer
- The term prompt engineer glosses over the idea that prompt formulation takes hypothesizing, research, result measurement, and repetition. Instead, approach prompting like a research project.
- Try as many different variations and formulations of your prompt as possible. One problem can have hundreds of solutions and one solution can have hundreds of approaches. The same can be said of prompting.